Container loading planning device, method, and program

Abstract

An input unit 81 receives an input of information on a container to be loaded, loading status of a freight car, and a container arrival prediction. A loading position determination unit 82 determines a loading position of the container to be loaded on a freight car based on a policy function, which is trained based on a past loading result or a loading plan, that calculates a selection probability of the loading position of the container assumed for the loading status of the freight car and a value function that calculates a value for the loading status of the freight car. And the loading position determination unit 82 determines the loading position of the container based on the value function calculated based on the container arrival prediction and the policy function.

What is claimed is: 
     
         1 . A container loading planning device comprising:
 a memory storing instructions; and   one or more processors configured to execute the instructions to:   receive an input of information on a container to be loaded, loading status of a freight car, and a container arrival prediction; and   determine a loading position of the container to be loaded on a freight car based on a policy function, which is trained based on a past loading result or a loading plan, that calculates a selection probability of the loading position of the container assumed for the loading status of the freight car and a value function that calculates a value for the loading status of the freight car,   wherein in determining the loading position of the container, the processor executes instructions to determine the loading position of the container based on the value function calculated based on the container arrival prediction and the policy function.   
     
     
         2 . The container loading planning device according to  claim 1 , wherein the processor further executes instructions to
 try multiple times, by a Monte Carlo tree search where a node corresponds to the loading position of the container, to search the loading position of the container that maximizes the value of a selection criterion of a node including the value function and the policy function in an order of arrival of the container indicated by the container arrival prediction to determine the loading position of the container.   
     
     
         3 . The container loading planning device according to  claim 2 , wherein the processor further executes instructions to
 determine the loading position corresponding to the node with the highest number of trials as the loading position of the container.   
     
     
         4 . The container loading planning device according to  claim 2 , wherein the processor further executes instructions to
 calculate a value of a first value function by trying a node corresponding to the loading position that maximizes the value of the selection criterion for a first container predicted from the container arrival prediction, calculate a value of a second value function by trying a lower node from the node corresponding to the tried loading position for a second container predicted after the first container, and add the value of the second value function to a value of the first value function of an upper node to update the value of the first value function of the upper node.   
     
     
         5 . The container loading planning device according to  claim 2 , wherein
 the selection criterion is defined such that the value of the value function is reduced and the value of the policy function is reduced for nodes with more trials.   
     
     
         6 . The container loading planning device according to  claim 1 , wherein the processor further executes instructions to
 calculate a policy distribution using Boltzmann distribution based on a trial result.   
     
     
         7 . A container loading planning method comprising:
 receiving an input of information on a container to be loaded, loading status of a freight car, and a container arrival prediction;   determining a loading position of the container to be loaded on a freight car based on a policy function, which is trained based on a past loading result or a loading plan, that calculates a selection probability of the loading position of the container assumed for the loading status of the freight car and a value function that calculates a value for the loading status of the freight car; and   in determining the loading position of the container, the loading position of the container is determined based on the value function calculated based on the container arrival prediction and the policy function.   
     
     
         8 . The container loading planning method according to  claim 7 , further comprising
 trying multiple times, by a Monte Carlo tree search where a node corresponds to the loading position of the container, to search the loading position of the container that maximizes the value of the selection criterion of a node including the value function and the policy function in an order of arrival of the container indicated by the container arrival prediction to determine the loading position of the container.   
     
     
         9 . A non-transitory computer readable information recording medium storing a container loading planning program, when executed by a processor, that performs a method for:
 receiving an input of information on a container to be loaded, loading status of a freight car, and a container arrival prediction; and   determining a loading position of the container to be loaded on a freight car based on a policy function, which is trained based on a past loading result or a loading plan, that calculates a selection probability of the loading position of the container assumed for the loading status of the freight car and a value function that calculates a value for the loading status of the freight car,   wherein the loading position of the container is determined based on the value function calculated based on the container arrival prediction and the policy function.   
     
     
         10 . The non-transitory computer readable information recording medium according to  claim 9 , further comprising a method for
 trying multiple times, by a Monte Carlo tree search where a node corresponds to the loading position of the container, to search the loading position of the container that maximizes the value of the selection criterion of a node including the value function and the policy function in an order of arrival of the container indicated by the container arrival prediction to determine the loading position of the container, in the loading position determination process.